Acute lymphoblastic leukemia (ALL) is the major pediatric cancer diagnosed in economically developed countries with B-cell precursor (BCP)-ALL, accounting for approximately 70% of ALL. Recent genome-wide association studies (GWAS) have provided the first unambiguous evidence for common inherited susceptibility to BCP-ALL, identifying susceptibility loci at 7p12.2, 9p21.3, 10q21.2, and 14q11.2. To identify additional BCP-ALL susceptibility loci, we conducted a GWAS and performed a meta-analysis with a published GWAS totaling 1658 cases and 4723 controls, with validation in 1449 cases and 1488 controls. Combined analysis identified novel loci mapping to 10p12.2 (rs10828317, odds ratio [OR] = 1.23; P = 2.30 × 10(-9)) and 10p14 marked by rs3824662 (OR = 1.31; P = 8.62 × 10(-12)). The single nucleotide polymorphism rs10828317 is responsible for the N215S polymorphism in exon 7 of PIP4K2A, and rs3824662 localizes to intron 3 of the transcription factor and putative tumor suppressor gene GATA3. The rs10828317 association was shown to be specifically associated with hyperdiploid ALL, whereas the rs3824662-associated risk was confined to nonhyperdiploid non-TEL-AML1 + ALL. The risk allele of rs3824662 was correlated with older age at diagnosis (P
The aim was to determine whether fed VLDL and chylomicron (CM) triacylglycerol (TAG) production rates are elevated in metabolic syndrome (MetS). Eight men with MetS (BMI 29.7 ± 1.1) and eight lean age-matched healthy men (BMI 23.1 ± 0.4) were studied using a frequent feeding protocol. After 4 h of feeding, an intravenous bolus of (2)H5-glycerol was administered to label VLDL1, VLDL2, and TAG. (13)C-glycerol tripalmitin was administered orally as an independent measure of CM TAG metabolism. Hepatic and intestinal lipoproteins were separated by an immunoaffinity method. In MetS, fed TAG and the increment in TAG from fasting to feeding were higher (P = 0.03 and P = 0.04, respectively) than in lean men. Fed CM, VLDL1, and VLDL2 TAG pool sizes were higher (P = 0.006, P = 0.03, and P
This paper consider cooperative localization in cellular networks. In this scenario, several located mobile terminals (MTs) are employed as reference nodes to find the location of an un-located MT. The located MTs sent training sequences in the uplink, then the un-located MT perform distance estimation using received signal strength techniques. The localization accuracy of the un-located MT is characterized in terms of squared position error bound (SPEB) . By taking into account the imperfect a priori location knowledge of the located MTs, the SPEB is derived in a closed-form. The closed-form indicate that the effect of the imperfect location knowledge on SPEB is equivalent to the increase of the variance of distance estimation. Moreover, based on the obtained closed-form, a MT selection scheme is proposed to decrease the number of located MTs sending training sequences, thus reduce the training overhead for localization. The simulation results show that the proposed scheme can reduce the training overhead with the paid of accuracy. and with the same training overhead, the accuracy of the proposed scheme is better than that of random selection. © 2011 IEEE.
Zhang Y, Ma Y, Tafazolli R (2007) Tighter bounds of symbol error probability for amplify-and-forward cooperative protocol over rayleigh fading channels, 2007 IEEE 18TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, VOLS 1-9 pp. 1920-1924 IEEE
Dammann A, Agapiou G, Bastos J, Brunel L, García M, Guillet J, Ma Y, Ma J, Nielsen JJ, Ping L, Raulefs R, Rodriguez J, Slock D, Yang D, Yi N (2013) WHERE2 Location aided communications, 19th European Wireless Conference, EW 2013
This paper presents an overview of preliminary results of investigations within the WHERE2 Project  on identifying promising avenues for location aided enhancements to wireless communication systems. The wide ranging contributions are organized according to the following targeted systems: cellular networks, mobile ad hoc networks (MANETs) and cognitive radio. Location based approaches are found to alleviate significant signaling overhead in various forms of modern communication paradigms that are very information hungry in terms of channel state information at the transmitter(s). And this at a reasonable cost given the ubiquitous availability of location information in recent wireless standards or smart phones. Location tracking furthermore opens the new perspective of slow fading prediction. © VDE VERLAG GMBH.
Lu Z, Ma Y, Cheraghi P, Tafazolli R (2013) Novel pilot-assisted spectrum sensing for OFDM systems by exploiting statistical difference between subcarriers, IEEE Transactions on Communications 61 (4) pp. 1264-1276
This paper presents a novel pilot-assisted spectrum sensing technique for orthogonal frequency-division multiplexing (OFDM) systems. The main idea is based upon the physical nature that subcarriers carrying pilots or payload data have different first-order and second-order statistical properties. These differences vanish when the spectrum of interest is unoccupied. Therefore, the decision of spectrum availability can be formed based upon these differences, which can be explored through employment of frequency-domain differential operations. Thanks to the differential operations, the proposed technique has less sensitivity of the noise power uncertainty problem caused by imperfect hardware. Performance of the proposed technique is analytically formulated in terms of probability of false alarm (PFA) and probability of detection (PD). Computer simulations are carried out to elaborate the analytical results. It is shown that the second-order statistics based proposed technique outperforms the conventional pilot-assisted technique up to 7 dB. Moreover, it is shown that the first-order statistics based proposed technique outperforms the second-order statistics based proposed technique for small normalized Doppler shifts (d 0.013). However, the second-order statistics based proposed technique offers better performance for larger normalized Doppler shifts. © 1972-2012 IEEE.
Yi N, Ma Y, Tafazolli R (2008) Multi-tone transmissions over two-user cognitive radio channel with weak interference, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
A transmitter with cognitive capability can sense talk between the other transmitter-receiver pairs. When this transmitter knows full or partial message of the others, it can choose an efficient strategy to access the transmission medium. This is referred to as cognitive radio channel. This work aims to investigate multi-tone transmission over two-user cognitive radio channels where cross-talk interference is weak. Cognitive transmitter (Tx1) is assumed to have full knowledge of message that is sent by the other transmitter (Tx2) to its corresponding receiver (Rx2). Channel capacity is carefully analyzed for frequency-selective scenarios. Efficient power-allocation strategies at Txl are investigated for various wireless environments. It is shown that Tx1 can find an efficient resource-accessing strategy if the channel gain of Tx1-Rx1 (the corresponding receiver) link is larger than the channel gain of Tx2-Rx2 link. In this case, the cognitive transmitter Tx1 can offer better performance by employing equal power allocation approach. Otherwise, it is not worthy for Txl to access transmission medium of Tx2-Rx2 link. © 2008 IEEE.
In this paper, we propose a rate-adaptive bit and power loading approach for the OFDM-based relaying communications. The cooperative relay operates in the half-duplex amplify-and-forward mode. The source and the relay has the separate power constraints. The maximum-ratio combining is employed at -the destination for maximizing the received SNR. Assuming the perfect channel knowledge available at all nodes, the proposed approach is to maximize the throughput (the number of bits/symbol) at the given power constraint and the target link performance. Unlike the water-filling method, the proposed approach does not need the iterative loading process, and can otTer the sub-optimum performance. Computer simulations are used to test the proposed approach for various scenarios with respect to the relay location or the distributed power allocation. © 2008 IEEE.
Cao A, Wang G, Ma Y, Xiao P, Tafazolli R Frequency Domain Pilot-based Carrier Frequency Offset Estimation in SC-FDMA system,
Yi N, Ma Y, Tafazolli R (2011) Incremental Decode-Forward Relaying over Asymmetric Fading Channels: Outage Probability and Location-Aided Relay Selection, pp. 181-184
This paper presents two contributions towards incremental decode-forward relaying over asymmetric fading channels. One is about the outage probability of incremental relay network accommodating i.n.d. cooperative paths. Our contribution is mainly on formulating a closed-form of the outage probability through employment of the Inverse Laplace Transform and Eular Summation. The other is about the proposal of transmit-power efficient relay-selection strategy through exploitation of the relationship between position of relays and the outage probability.
He Z, Ma Y, Tafazolli R (2013) Improved high resolution TOA estimation for OFDM-WLAN based indoor ranging, IEEE Wireless Communications Letters 2 (2) pp. 163-166
This letter presents three novel approaches, namely peak detection, modified maximum peak-to-leaking ratio detection and channel frequency response (CFR) reconstruction, in order to improve the high resolution TOA estimation technique when using OFDM-based WLAN preamble. Computer simulations show that all the proposed approaches outperform the state-of-the-art in the WINNER A1 LOS channel. Moreover, the proposed approaches demonstrate their advantages in WARP2 board based Wi-Fi testbed. © 2012 IEEE.
He Z, Ma Y, Tafazolli R (2012) Opportunistic Cooperative Positioning in OFDMA Systems, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences Vol.E95-A (9) pp. 1642-1645 IEICE
This letter presents a novel opportunistic cooperative positioning approach for orthogonal frequency-division multiple access (OFDMA) systems. The basic idea is to allow idle mobile terminals (MTs) opportunistically estimating the arrival timing of the training sequences for uplink synchronization from active MTs. The major advantage of the proposed approach over state-of-the-arts is that the positioning-related measurements among MTs are performed without the paid of training overhead. Moreover, Cramer-Rao lower bound (CRLB) is utilized to derive the positioning accuracy limit of the proposed approach, and the numerical results show that the proposed approach can improve the accuracy of non-cooperative approaches with the a-priori stochastic knowledge of clock bias among idle MTs.
Cheraghi P, Ma Y, Tafazolli R (2011) Frequency-domain differential energy detection based on extreme statistics For OFDM source sensing, IEEE Vehicular Technology Conference
This paper presents a novel differential energy detection scheme based on extremes of order statistics for sensing OFDM signals. The underlying initiative of this approach is applying the order statistics of the differential Energy Spectral Density in frequency domain. The proposed technique takes advantage of the channel selectivity which is inherited from high data-rate communications. The introduced frequency diversity allows this approach to meet FCC requirements even in low SNR environments i.e., (-25,-10) dB. Analytical results of sensing performance are provided in terms of both probability of false alarm and probability of detection. Furthermore, computer simulations show that the proposed technique outperforms two most commonly used source detection approaches namely conventional energy detection and cyclostationarity based detection for up to 10 dB gain in low SNR environments. © 2011 IEEE.
This letter presents a new posterior Cramér-Rao bound (PCRB) for inertial sensors enhanced mobile positioning, which performs hybrid data fusion of parameters including position estimates, pedestrian step size, pedestrian heading, and the knowledge of random walk motion model. Moreover, a non-matrix closed form of the PCRB is derived without position estimates. Finally, our numerical results show that when the accuracy of step size and heading measurements is high enough, the knowledge of random walk model becomes redundant.
Liu H, Ma Y, Tafazolli R (2008) Optimum pilot placement for chunk-based OFDMA uplink: Time direction scenario, 2008 IEEE 67TH VEHICULAR TECHNOLOGY CONFERENCE-SPRING, VOLS 1-7 pp. 2547-2551 IEEE
Qian C, Ma Y, Tafazolli R (2013) On spectral efficiency of using relay with opportunistic channel assignment, GLOBECOM - IEEE Global Telecommunications Conference pp. 943-948
Relay with opportunistic channel assignment (OCA) is an intermediate wireless node, which forwards messages through temporarily unused licensed channels. The spectral efficiency of OCA relay largely depends on the channel usage. This paper shows that, with a practical model of channel usage, the OCA relay outperforms the relay with fixed channel assignment by up to 0.8 bits/s/Hz/user. This interesting result is observed through our extensive investigation of the demodulation-and-forward relay adopting various resource allocation algorithms, which include the round-robin, joint channel and power allocation, best-user selection, and combinations of them. Moreover, the communication delay of all the considered OCA relaying schemes is evaluated through Monte Carlo simulations. © 2013 IEEE.
He Z, Ma Y, Tafazolli R (2013) Indoor TDOA mobile positioning with clock drift and its cramér-rao bound, 19th European Wireless Conference, EW 2013
The paper presents a time-difference-of-arrival (TDOA) position estimation algorithm for indoor positioning in the present of clock drift in a mobile terminal. Then, a new Cramér-Rao bound is derived as a benchmark of the algorithm. The simulation results show that an acceptable positioning accuracy can be achieved when at least five access points in wireless local area networks are involved in positioning. Moreover, when the clock drift or the TDOA is considerably large, the proposed algorithm outperforms the algorithm without considering the clock drift. © VDE VERLAG GMBH.
Movahedian M, Ma Y, Tafazolli R (2008) An MUI resilient approach for blind CFO estimation in OFDMA uplink, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Liu H, Ma Y, Tafazolli R (2007) Optimum pilot placement for chunk-based OFDMA uplink: Single chunk scenario, 2007 IEEE 66TH VEHICULAR TECHNOLOGY CONFERENCE, VOLS 1-5 pp. 2194-2198 IEEE
Hou J, Ma Y, Yi N, Tafazolli R (2014) Reduced-complexity coordinated beamforming for multicell downlink max-min SINR problem, IEEE Wireless Communications Letters 3 (4) pp. 353-356
This letter presents a reduced-complexity algorithm for coordinated beamforming aimed at solving the multicell downlink max-min signal-to- interference-plus-noise problem under per-base-station power constraints. It is shown that the proposed algorithm can achieve close performance to the optimum algorithm with faster convergence and lower complexity. © 2014 IEEE.
He Z, Ma Y, Tafazolli R (2012) Training Convergence in Range-based Cooperative Positioning with Stochastic Positional Knowledge, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E95.A (7) pp. 1200-1204 IEICE
This letter investigates the training convergence in range-based cooperative positioning with stochastic positional knowledge. Firstly, a closed-form of squared position-error bound (SPEB) is derived with error-free ranging. Using the derived closed-form, it is proved that the SPEB reaches its minimum when at least 2 out of N(>2) agents send training sequences. Finally, numerical results are provided to elaborate the theoretical analysis with zero-mean Gaussian ranging errors.
Yi N, Ma Y, Tafazolli R (2011) Cooperative iterative water-filling for two-user Gaussian frequency-selective interference chanels,
In this paper, a cooperative iterative water-filling approach is investigated for two-user Gaussian interference channel. State-of-the-art approaches only maximize the individual user's own rate and always model interference as noise. Our proposed approach establishes user cooperation through sharing network side information. It iteratively maximizes the sum-rate of both users subject to distributed power constraint. Interference is optimally regarded as message or noise. Three efficient rate-sharing schemes are also investigated between two users based on priority. Numerical results are performed in frequency-selective environment. It is observed that the proposed approach offers significantly performance improvement in comparison with conventional iterative water-filling approaches.
Spectrum sensing is one of key enabling techniques to advanced radio technologies such as cognitive radios and ALOHA. This paper presents a novel non-cooperative spectrum sensing approach that can achieve a good trade-off between latency, reliability and computational complexity. Our major idea is to exploit the first-order cyclostationarity of the primary user's signal to reduce the noise-uncertainty problem inherent in the conventional energy detection approach. It is shown that the proposed approach is suitable for detecting the primary user's activity in the interweave paradigm of cognitive spectrum sharing, while the active primary user is periodically sending training sequence. Computer simulations are carried out for the typical IEEE 802.11g system. It is observed that the proposed approach outperforms both the energy detection and the second-order cyclostationarity approach when the observation period is more than 10 frames corresponding to 0.56 ms. ©2010 IEEE.
Qian C, Chen H, Ma Y, Tafazolli R (2013) A novel adaptive hybrid-ARQ protocol for machine-to-machine communications, IEEE Vehicular Technology Conference
Emerging low date-rate Machine-to-Machine (M2M) communications call for promising Hybrid Automatic Repeat-reQuest (HARQ) schemes with improved link reliability and feedback efficiency. This motivates us to develop a novel adaptive HARQ scheme by exploiting the knowledge of Channel Quality Information (CQI), which can be obtained through either channel estimation techniques or location-aided technology. The proposed adaptive HARQ scheme will determine the suitable transmission mode to guarantee a specific Frame Error Rate (FER) during the first transmission with the aid of location information. Simulation results demonstrated that our proposed scheme can achieve more attractive throughput performance, while maintaining a similar FER, compared to conventional HARQ schemes. © 2013 IEEE.
Lu Z, Ma Y, Cheraghi P, Tafazolli R (2013) Novel Pilot-Assisted Spectrum Sensing for OFDM Systems by Exploiting Statistical Difference Between Subcarriers, IEEE Transactions on Communications
This paper presents a novel pilot-assisted spectrum sensing technique for orthogonal frequency-division multiplexing (OFDM) systems. The main idea is based upon the physical nature that subcarriers carrying pilots or payload data have different first-order and second-order statistical properties. These differences vanish when the spectrum of interest is unoccupied. Therefore, the decision of spectrum availability can be formed based upon these differences, which can be explored through employment of frequency-domain differential operations. Thanks to the differential operations, the proposed technique has less sensitivity of the noise power uncertainty problem caused by imperfect hardware. Performance of the proposed technique is analytically formulated in terms of probability of false alarm (PFA) and probability of detection (PD). Computer simulations are carried out to elaborate the analytical results. It is shown that the second-order statistics based proposed technique outperforms the conventional pilot-assisted technique up to 7 dB. Moreover, it is shown that the first-order statistics based proposed technique outperforms the second-order statistics based proposed technique for small normalized Doppler shifts (d 0.013). However, the second-order statistics based proposed technique offers better performance for larger normalized Doppler shifts.
Hou J, Ma Y, Tafazolli R (2011) Joint power and interference trade-off for underlay cognitive beamforming technique, 17th European Wireless Conference 2011, EW 2011 pp. 587-591
Underlay cognitive beamforming allows secondary transmitters to suppress interferences to the primary users, whilst maintain their own quality of services. This paper aims at investigating joint power and interference trade-off inherent in the underlay cognitive beamforming scheme. It is shown that the work of interests leads to a non-convex optimization problem, which can be resolved by employing the second-order cone programming. It is theoretically proved that introducing zero-interference to the primary user does not always lead to the system optimality; moreover, we exhibit two conditions, for which the interference should be treated as noise in order to maximize the sum-rate of the considered beamforming system. © VDE VERLAG GMBH.
Liu H, Ma Y, Tafazolli R (2007) Sub-optimum pilot placement for chunk-based OFDMA uplink: Consecutive chunks scenario, 2007 IEEE 18TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS, VOLS 1-9 pp. 1925-1929 IEEE
Yi N, Ma Y, Tafazolli R (2013) Joint rate adaptation and best-relay selection using limited feedback, IEEE Transactions on Wireless Communications 12 (6) pp. 2797-2805
This paper presents a novel joint rate adaptation and relay selection scheme for multi-relay networks adopting half-duplex best-relay decode-and-forward protocol. The proposed scheme aims to maximize the overall transmission rate when relays are allowed to forward messages using different rates from the source. It is shown that the proposed scheme outperforms the conventional adaptive scheme in terms of the spectral efficiency (e.g. by 10.1% improvement for SNR=10 dB). Furthermore, in order to reduce signaling overhead of the proposed scheme, a number of joint discrete-rate adaptation and relay selection approaches are proposed for both non-reciprocal and reciprocal channels. The relay selection is basically a two-stage scheme. At the rm first stage, a set of relays are selected based on mixed channel quality information (CQI), i.e., the knowledge of CQI varies for different links; at the second stage, the best relay within the set is selected based on instantaneous CQI, which is obtained through carefully designed signaling protocols. It is shown that the proposed discrete-rate adaptation schemes can offer comparable spectral efficiency to the conventional adaptive scheme with significantly reduced signaling overhead. © 2002-2012 IEEE.
Yngvesson HEA, Ma Y, Yi N, Tafazolli R (2013) Transmit antenna selection in a cognitive MIMO system with primary cooperation, GLOBECOM - IEEE Global Telecommunications Conference pp. 931-936
In this paper a multiple-input multiple-output (MIMO) cognitive system is investigated. In this setting the receivers in the primary user (PU) group null interference with the application of zero-forcing (ZF) filters and the transmit signals are adapted to meet individual rate constraints. The objective is to maximize the rate of the secondary user (SU), subject to a SU power constraint and individual PU rate constraints. Since the PU receiver cooperates with the SU by actively reserving part of its receive space for interference, the problem critically depends on the feasibility of the PU ZF operation and this in turn translates into a restriction on the number of SU transmit antennas. To investigate the behavior of the system in terms of SU rate and PU power sacrifice a SU transmit antenna selection method is proposed. It is demonstrated that PU cooperation enables SU communication in situations where transmit zero-forcing beamforming or opportunistic interference alignment (OIA) remains infeasible. In addition, simulation results highlight the advantage of PU cooperation over OIA in situations where the SU only just has enough transmit antennas to perform OIA. © 2013 IEEE.
Luo H, Ma Y, Evans BG (2009) A Spectral Efficient Decode-and-Forward Relaying Scheme for Satellite Broadcast Networks, 2009 INTERNATIONAL WORKSHOP ON SATELLITE AND SPACE COMMUNICATIONS, CONFERENCE PROCEEDINGS pp. 252-256 IEEE
Liu H, Ma Y, Tafazolli R (2008) On efficiency gain of joint pilot and data adaptation for OFDM based systems, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
The aim of this article is to share a novel concept termed pseudo pilot, which offers a simple and ef?cient approach of non-pilot-assisted channel estimation. Our key idea is to transfer the uncertainty of several payload symbols into the uncertainty of symbol interleavers by employing a bank of interleavers at the transmitter. Those uncertainty-transferred symbols serve as pseudo pilots for the receiver to perform channel estimation. The uncertainty of symbol interleavers is then removed in the procedure of decoding. Performance and scalability of the pseudo pilot technique are evaluated through both theoretical analysis and computer simulations.
The problem of spectrum sharing by exploiting the spatial domain is investigated in this thesis. The ultimate purpose of such a scheme is to mitigate the under-utilization of the scarce spectrum resource. By taking into account the availability of multiple antennas at the communicating nodes, an additional level of freedom can be exploited. Multiple-input multiple-output antenna systems have previously been shown to hold great promise: a linear growth in capacity without bandwidth expansion, enhanced transmission reliability using for instance space-time codes, and effective interference handling.
The question of how these properties can be harnessed is explored by considering two perspectives: no cooperation and cooperation between users. For the cooperative scenario, a spatial-domain interweave spectrum sharing scheme is introduced that enables opportunistic transmission at a controlled cost to the license holders. The proposed scheme demonstrates three excellent characteristics: that exploitation of the spatial domain allows opportunistic communication in a ?spatial hole,? that spectrum sharing is effectively enabled by inter-tier cooperation, and finally that in this scenario spatial-domain interweave is feasible with a ?small? (as compared to the number of receive antennas at the incumbent) number of transmit antennas. In essence, this opens the possibility of the incumbents? performance to be traded against opportunistic transmission. In the non-cooperative scenario, a spectrum sharing model between a small and large MU-MIMO system is proposed and analysed. The significant service antenna number asymmetry poses unique challenges and opportunities. In the limit of an infinite number of service antennas at one of the access point, the interference and noise power tends to zero and the transmit power can also be scaled back accordingly. These traits seem ideal for use in a spectrum sharing scenario, but in the present case with the coexistence of a conventional MIMO system and with a finite number of service antennas, how will the system behave? The resulting interference scenario is analysed explicitly both in the uplink and downlink, assuming linear receive and transmit equalizers, respectively. Characterization of the mean SINR operating point and required transmit power are presented, and concise transmit power scaling laws are derived. The scaling laws offer insight into how the system behaves with the number of service antennas and system load.
Multiuser multiple-input multiple-output (MU-MIMO) has the potential to substantially increase the uplink network efficiency by multiplexing the user terminals' (UTs) transmissions in the spatial domain. However, demultiplexing the transmissions at the network side, known as MU-MIMO detection, can become a considerable signal processing challenge, especially in cases with a high spatial user load. During the last two decades, the MIMO detection problem has been extensively studied, and many receiver designs have been proposed that offer very good tradeoffs in complexity vs. performance. Nevertheless, MU-MIMO detection still presents challenges in signal processing scalability in the system size and modulation order. We revisit this problem but through an alternative method of joint transmitter and receiver design. Two approaches that exhibit near-optimal reliability and low complexity are presented:
First, a technique that uses real-valued modulation in fully- and over-loaded cases in large MU-MIMO systems, where there are equal or more UTs than service antennas. It is seen that the use of real constellations with a widely linear equaliser benefits from an increased spatial diversity gain over complex constellations with a linear equaliser. Moreover, a likelihood ascent search (LAS) algorithm post-processing stage is applied to further improve the error performance. Computer simulations show remarkable results for large MU-MIMO sizes in uncoded or coded cases.
Second, recognising that real-valued modulation offers poor modulation efficiency, a real-complex hybrid modulation (RCHM) scheme is proposed, where a mix of real- and complex-valued symbols are interleaved in the spatial and temporal domains. It is seen that RCHM combines the merits of real and complex modulations and enables the adjustment of the diversity-multiplexing tradeoff. Through the system outage probability analysis, the optimal ratio of the number real-to-complex symbols, as well as their optimal power allocation, is found for the RCHM pattern. Furthermore, reliability is improved with a small expense in complexity through the use of a successive interference cancellation (SIC) stage. Results are validated through the mathematical analysis of the average bit error rate and through computer simulations considering single and multiple base station scenarios, which show SNR gains over conventional approaches in excess of 5 dB at 1% BLER.
The results suggest that an expense in complexity is not the only way to improve error performance, but near-optimal reliability is also possible using simple techniques through a reduction in the multiplexing gain. Therefore, rather than a two-way complexity vs. performance tradeoff in MU-MIMO detection, a three-way tradeoff may be more appropriate, and is roughly expressed in the following statement:
?Low complexity, high reliability, high multiplexing gain: choose two.?
In this paper, a novel approach, namely realcomplex
hybrid modulation (RCHM), is proposed to scale up
multiuser multiple-input multiple-output (MU-MIMO) detection
with particular concern on the use of equal or approximately
equal service antennas and user terminals. By RCHM, we mean
that user terminals transmit their data sequences with a mix of
real and complex modulation symbols interleaved in the spatial
and temporal domain. It is shown, through the system outage
probability, RCHM can combine the merits of real and complex
modulations to achieve the best spatial diversity-multiplexing
trade-off that minimizes the required transmit-power given a
sum-rate. The signal pattern of RCHM is optimized with respect
to the real-to-complex symbol ratio as well as power allocation.
It is also shown that RCHM equips the successive interference
canceling MU-MIMO receiver with near-optimal performances
and fast convergence in Rayleigh fading channels. This result is
validated through our mathematical analysis of the average biterror-
rate as well as extensive computer simulations considering
the case with single or multiple base-stations.
This paper proposes a novel carrier frequency offset (CFO)
estimation method for generalized MC-CDMA systems in unknown frequency-selective channels utilizing hidden pi-
lots. It is established that CFO is identifiable in the frequency domain by employing cyclic statistics (CS) and linear re-gression (LR) algorithms. We show that the CS-based estimator is capable of mitigating the normalized CFO (NCFO) to a small error value. Then, the LR-based estimator can be employed to offer more accurate estimation by removing the residual quantization error after the CS-based estimator.
In this paper, a symbol-level selective transmission
for full-duplex (FD) relaying networks is proposed to mitigate
error propagation effects and improve system spectral efficiency.
The idea is to allow the FD relay node to predict the correctly
decoded symbols of each frame, based on the generalized square
deviation method, and discard the erroneously decoded symbols,
resulting in fewer errors being forwarded to the destination node.
Using the capability for simultaneous transmission and reception
at the FD relay node, our proposed strategy can improve the
transmission efficiency without extra cost of signalling overhead.
In addition, targeting on the derived expression for outage probability,
we compare it with half-duplex (HD) relaying case, and
provide the transmission power and relay location optimization
strategy to further enhance system performances. The results
show that our proposed scheme outperforms the classic relaying
protocols, such as cyclic redundancy check based selective
decode-and-forward (S-DF) relaying and threshold based SDF
relaying in terms of outage probability and bit-error-rate.
Moreover, the performances with optimal power allocation are
better than those with equal power allocation, especially when
the FD relay node encounters strong self-interference and/or it
is close to the destination node.
The aim of this paper is to handle the multifrequency
synchronization problem inherent in orthogonal
frequency-division multiple access (OFDMA) uplink
communications, where the carrier frequency offset (CFO)
for each user may be different, and they can be hardly
compensated at the receiver side. Our major contribution
lies in the development of a novel OFDM receiver that
is resilient to unknown random CFO thanks to the use
of a CFO-compensator bank. Specifically, the whole CFO
range is evenly divided into a set of sub-ranges, with
each being supported by a dedicated CFO compensator.
Given the optimization for CFO compensator a NP-hard
problem, a machine deep-learning approach is proposed
to yield a good sub-optimal solution. It is shown that the
proposed receiver is able to offer inter-carrier interference
free performance for OFDMA systems operating at a wide
range of SNRs.
This work aims to handle the joint transmitter
and noncoherent receiver optimization for multiuser single-input
multiple-output (MU-SIMO) communications through unsupervised
deep learning. It is shown that MU-SIMO can be modeled
as a deep neural network with three essential layers, which
include a partially-connected linear layer for joint multiuser
waveform design at the transmitter side, and two nonlinear layers
for the noncoherent signal detection. The proposed approach
demonstrates remarkable MU-SIMO noncoherent communication
performance in Rayleigh fading channels.
Considering a densely populated area where
a mobile device, with a single RF chain, shares its message
with a set of mobile devices through narrowband mmWave
channel, an analogue-beam splitting approach is proposed
to achieve a good capacity and coverage trade-off. The
proposed approach aims at maximizing the capacity of
the mmWave multicast channel through antenna-element
grouping and adaptive phase shifting, which takes into
account of the inter-beam interference. When receivers are
randomly distributed on a circle centered at the transmitter,
according to the uniform distribution, it is found
that the impact of inter-beam interference on the channel
capacity can be negligibly small, and thus the analoguebeam
splitting approach can be largely simplified in practice.
Computer simulations are carried out to elaborate our
theoretical study and demonstrate considerable advantages
of the proposed analogue-beam splitting approach.
In this paper, a novel unsupervised deep learning
approach is proposed to tackle the multiuser frequency synchronization
problem inherent in orthogonal frequency-division
multiple-access (OFDMA) uplink communications. The key idea
lies in the use of the feed-forward deep neural network (FF-DNN)
for multiuser interference (MUI) cancellation taking advantage
of their strong classification capability. Basically, the proposed
FF-DNN consists of two essential functional layers. One is
called carrier-frequency-offsets (CFOs) classification layer that
is responsible for identifying the users? CFO range, and another
is called MUI-cancellation layer responsible for joint multiuser
detection (MUD) and frequency synchronization. By such means,
the proposed FF-DNN approach showcases remarkable MUIcancellation
performances without the need of multiuser CFO
estimation. In addition, we also exhibit an interesting phenomenon
occurred at the CFO-classification stage, where the
CFO-classification performance get improved exponentially with
the increase of the number of users. This is called multiuser
diversity gain in the CFO-classification stage, which is carefully
studied in this paper.
In this paper, unsupervised deep learning solutions
for multiuser single-input multiple-output (MU-SIMO) coherent
detection are extensively investigated. According to the ways
of utilizing the channel state information at the receiver side
(CSIR), deep learning solutions are divided into two groups.
One group is called equalization and learning, which utilizes the
CSIR for channel equalization and then employ deep learning for
multiuser detection (MUD). The other is called direct learning,
which directly feeds the CSIR, together with the received signal,
into deep neural networks (DNN) to conduct the MUD. It is found
that the direct learning solutions outperform the equalizationand-
learning solutions due to their better exploitation of the
sequence detection gain. On the other hand, the direct learning
solutions are not scalable to the size of SIMO networks, as
current DNN architectures cannot efficiently handle many cochannel
interferences. Motivated by this observation, we propose
a novel direct learning approach, which can combine the merits
of feedforward DNN and parallel interference cancellation. It is
shown that the proposed approach trades off the complexity for
the learning scalability, and the complexity can be managed due
to the parallel network architecture.
This paper presents a parallel computing approach
that is employed to reconstruct original information bits from
a non-recursive convolutional codeword in noise, with the goal
of reducing the decoding latency without compromising the
performance. This goal is achieved by means of cutting a
received codeword into a number of sub-codewords (SCWs)
and feeding them into a two-stage decoder. At the first stage,
SCWs are decoded in parallel using the Viterbi algorithm or
equivalently the brute force algorithm. Major challenge arises
when determining the initial state of the trellis diagram for each
SCW, which is uncertain except for the first one; and such results
in multiple decoding outcomes for every SCW. To eliminate or
more precisely exploit the uncertainty, an Euclidean-distance
minimization algorithm is employed to merge neighboring SCWs;
and this is called the merging stage, which can also run in
parallel. Our work reveals that the proposed two-stage decoder
is optimal and has its latency growing logarithmically, instead
of linearly as for the Viterbi algorithm, with respect to the
codeword length. Moreover, it is shown that the decoding latency
can be further reduced by employing artificial neural networks
for the SCW decoding. Computer simulations are conducted
for two typical convolutional codes, and the results confirm our
Deep learning is driving a radical paradigm shift in wireless communications, all the way from the application layer down to the physical layer. Despite this, there is an ongoing debate as to what additional values artificial intelligence (or machine learning) could bring to us,
particularly on the physical layer design; and what penalties there may have? These questions motivate a fundamental rethinking of the wireless modem design in the artificial intelligence era. Through several physical-layer case studies, we argue for a significant role that machine learning could play, for instance in parallel error-control coding and decoding, channel equalization, interference cancellation,
as well as multiuser and multiantenna detection. In addition, we will also discuss the fundamental bottlenecks of machine learning as
well as their potential solutions in this paper.
In this paper, the real-time deployment of unmanned
aerial vehicles (UAVs) as flying base stations (BSs) for
optimizing the throughput of mobile users is investigated for UAV networks. This problem is formulated as a time-varying mixed-integer non-convex programming (MINP) problem, which is challenging to find an optimal solution in a short time with conventional optimization techniques. Hence, we propose
an actor-critic-based (AC-based) deep reinforcement learning (DRL) method to find near-optimal UAV positions at every moment. In the proposed method, the process searching for the solution iteratively at a particular moment is modeled as a Markov decision process (MDP). To handle infinite state and action spaces and improve the robustness of decision process, two powerful neural networks (NNs) are configured to evaluate
the UAV position adjustments and make decisions, respectively. Compared with heuristic, sequential least-squares programming and fixed methods, Simulation results have shown that the proposed method outperforms in terms of the throughput at every moment in UAV networks.
In this paper, single-input multiple-output (SIMO)
system when employing massive binary array-receiver has been investigated while constructive noise has been observed in the single user system to detect the higher-order QAM modulated signals. To fully understand the interesting phenomenon, mathematical
model has been established and analyzed in this paper.
Theorems of the signal detectability are studied to understand the best operating signal-to-noise ratio (SNR) range based on the error behaviours of the single user SIMO system. Within the observation and analysis, a novel new multiuser SIMO with binary array-receiver structure has been proposed and can be considered as a solution to deal with the high complexity problem
that the traditional model has when using maximum likelihood (ML) detection. The key idea of this approach is to set up the multiuser multiple-input multiple-output (MIMO) model into a frequency division multiple access (FDMA) scenario and regard each user as single user SIMO to achieve the goal of decreasing
the exponentially increased complexity of ML detection method to the number of users. It is shown by numerical results that each user in this system can achieve a promising error behaviour in
the specific best operating SNR range.
In this paper, an orthogonal stochastic gradient
descent (O-SGD) based learning approach is proposed to
tackle the wireless channel over-training problem inherent in artificial neural network (ANN)-assisted MIMO signal detection. Our basic idea lies in the discovery and exploitation of the training-sample orthogonality between the current training epoch and past training epochs. Unlike the conventional SGD that updates the neural network simply based upon current training samples, O-SGD discovers the correlation
between current training samples and historical training
data, and then updates the neural network with those
uncorrelated components. The network updating occurs
only in those identified null subspaces. By such means, the neural network can understand and memorize uncorrelated components between different wireless channels, and thus is more robust to wireless channel variations. This hypothesis is confirmed through our extensive computer simulations as well as performance comparison with the conventional SGD
Multi-access edge computing for mobile computingtask
offloading is driving the extreme utilization of available degrees of freedom (DoF) for ultra-reliable low-latency downlink communications. The fundamental aim of this work is to find latency-constrained transmission protocols that can achieve a very-low outage probability (e.g. 0:001%). Our investigation is mainly based upon the Polyanskiy-Poor-Verd´u formula on the finite-length coded channel capacity, which is extended from the
quasi-static fading channel to the frequency selective channel. Moreover, the use of a suitable duplexing mode is also critical to the downlink reliability. Specifically, time-division duplexing
(TDD) outperforms frequency-division duplexing (FDD) in terms of the frequency diversity-gain. On the other hand, FDD takes the advantage of having more temporal DoF in the downlink, which can be exchanged into the spatial diversity-gain through the use of space-time coding. Numerical study is carried out to compare the reliability between FDD and TDD under various latency constraints.